September 17, 2025Frontiers in MedicineOpen Access

Risk prediction of osteoporotic vertebral compression fractures in postmenopausal osteoporotic women by machine learning modelling

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Retrospective case-control study identifies key risk factors for vertebral fractures, suggesting machine learning enhances prediction accuracy.

The machine learning model predicts osteoporotic vertebral compression fractures with an accuracy of 98.98%.
Low bone mineral density, chronic inflammation, and sarcopenia are significant independent risk factors for fractures.
Retrospective case-control study analyzed 486 postmenopausal women between 2015 and 2018 to identify fracture risks.
The findings emphasize the need for future large-scale studies to validate the predictive model and improve risk management.

Sun et al. (2025) studied this question.

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September 17, 2025Frontiers in MedicineOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Retrospective case-control study identifies key risk factors for vertebral fractures, suggesting machine learning enhances prediction accuracy.

The machine learning model predicts osteoporotic vertebral compression fractures with an accuracy of 98.98%.
Low bone mineral density, chronic inflammation, and sarcopenia are significant independent risk factors for fractures.
Retrospective case-control study analyzed 486 postmenopausal women between 2015 and 2018 to identify fracture risks.
The findings emphasize the need for future large-scale studies to validate the predictive model and improve risk management.

Sun et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark